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Spss Essay

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Intermediate SPSS (1) Hypothesis Testing and Inferential Statistics Tutorial Goal: Building and testing hypotheses using inferential statistics in SPSS. This workshop covers parametric and nonparametric tests, concentrating on correlation, chi-square, and t-tests. Participants learn how to understand, analyze and report results. Ok, let’s review somewhat from our last workshop. What is statistics? First, what is statistics? “Statistics is the science and practice of developing knowledge through the use of empirical data expressed in quantitative form (http://www.answers.com/topic/statistics-2?method=6).” So, you are basically posing a question about something in the Social Sciences and using numbers to answer it. Some examples of these questions are: Do countries with stricter gun control laws have fewer deaths by firearms? What are the best methods for teaching? What factors cause a disease to spread from one place to another? Do religious views and class affect opinions about euthanasia? You can answer these questions by using numbers. For statistics, there are four kinds of levels of measurement for the variable. All your analyses extend from what kind of level your variable is. They are NOIR. (N)ominal (O)rdinal (I)nterval (R)atio Let’s talk about each one. Nominal means that the number simply represents a category of objects. There is no measured different among the objects or people. Some examples are giving states numbers (N.Y. 1, Connecticut 2, R.I. 3), assigning a number for gender (male 1, female 2), or designating college major (History 1, Business 2, Sociology 3). You are just assigning a number to something. Ordinal means the larger number for the object is truly larger in some sort of amount. This typically means rank. Some examples are 1st, 2nd, and 3rd places in a contest, or preferences for different movies. However, there is no exactly measured difference among the objects. We don’t know definitively how much larger or better 1st is compared to...